Contents
What do you need to know about competing risk analysis?
1 Overview. Competing risk analysis refers to a special type of survival analysis that aims to correctly estimate marginal probability of an event in the presence of competing events. 2 Description. What is “competing event” and “competing risk”? 3 Readings. J.
How is the CIF used in a competing risk analysis?
Like many analyses, the competing risk analysis includes a non-parametric method which involves the use of a modified Chi-squared test to compare CIF curves between groups, and a parametric approach which model the CIF based on a subdistribution hazard function.
Can a fine and gray model be used for a competing risk analysis?
The Fine and Gray model can also be extended to allow for time-dependent covariates. Today, analysis of competing data using either non-parametric or parametric method is available in the major statistical packages including R , STATA and SAS.
How is the probability of a competing event regulated?
As a result, we call the probability of these events as “competing risks”, in a sense that the probability of each competing event is somehow regulated by the other competing events, which has an interpretation suitable to describe the survival process determined by multiple types of events.
Can a covariate of an event affect a competing risk?
However, the effect of a covariate on an event from either a cause-specific (e.g., relapse) model or cause nonspecific (e.g., relapse and TRM combined) model may be very different from the effect of the covariate of the event (e.g., relapse) in the presence of competing risks (e.g., TRM).
What is the object of a competing event analysis?
Like in standard survival analysis, the analytical object for competing event data is to estimate the probability of one event among the many possible events over time, allowing the subjects to fail from competing events.
How is km estimator used in competing event analysis?
Likewise, in competing event data, the typical approach involves the use of KM estimator to separately estimate probability for each type of event, while treating the other competing events as censored in addition to those who are censored from loss to follow-up or withdrawal.